The present invention relates to the diagnostic imaging arts. It finds particular application in conjunction with a CT imaging system and will be described with particular reference thereto. However, it is to be appreciated that the present invention is applicable to a wide range of diagnostic imaging modalities.
In the field of medical imaging, it is often necessary to recognize changes of the object to be examined on the basis of different images of the same object. It is often desired that the images acquired at different instances should enable the physician to recognize which of the changes appearing in the imaged object are due to natural motions and deformations and which changes can be attributed to pathological changes such as, for example, tumor growth. Images of a subject which have been formed before and after an operation or treatment are routinely compared so as to assess the result of the treatment.
Typically, the images, which are formed at different instances by the same or different modalities, have to be registered by the means of scaling, rotating and the like to have the position and shape of the organs coincide. Rigid transformations are defined as geometrical transformations that preserve distances. The rigid transformations also preserve straightness of lines and all non-zero angles between straight lines. The rigid transformations are typically composed of translations and rotations. When the bending of joints and the respiratory motion constitute flexible or non-rigid motions, the anatomical object to be examined cannot be shifted to its original position by rigid transformations such as rotation and translation. In this case, an elastic registration is typically used.
In elastic registration, the image is modeled as an elastic body and the similarity between points or features in the two images act as external forces, which stretch the body. Elastic registration of images is used for a wide variety of clinical applications where images that have been acquired at different times, with different modalities, or for different patients need to be aligned with one another. The examples of images requiring elastic transformation include tumor diagnosis, surgery and treatment, where the images are typically taken at different modalities to show different aspects of the tumor, taken at different times to compare effects of pre-intervention and post-intervention images, or being matched with the anatomical atlases derived from cohorts studies.
Typically, the images are first segmented to designate a region of interest to guide the registration. After the images are segmented and common points to the two images are established, the images are registered by using the rigid transformation, as step one; and the elastic transformation, as step two. Because of the complexity of the elastic transformations, sometimes the image structures are not properly aligned. In this case, it is desirable that the user manually corrects the registration, following the elastic transform registration, by introducing deformations to the segmented surfaces in the 3D images. Generally, the manual correction of the 3D images registration is difficult as the 3D datasets include large volumes of data to be transformed following the manual deformation.
The present application contemplates a new and improved method and apparatus which overcomes the above-referenced problems and others.